Prediction of the Yield Per Hectare of the Crop of Chili Pepper (Capsicumchinense), by Means of a Simulation Model with GIS. A Case Study in Santo Domingo - San Jacinto Del Bua

The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The multi-method simulation model leverages and shows the effect of the physics-based data (deterioration curves), loading profiles, and detection and prediction levels. It is concluded that implementing intelligent maintenance without an effective predictive horizon of the associated PdM and effective frequency of opportunistic maintenance intervals, does not guarantee the gain of its lifetime benefits. Moreover, the case study maintenance data shall be collected in a complete (no missing data) and more accurate manner (use hours instead of date only) and used to continuously upgrade the failure rates and maintenance times.

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A Practical Approach to Expedite a Pore to Process Simulation Model for a Rich Gas Condensate Reservoir – Case Study

10.2118/205138-ms ◽

2021 ◽

Author(s):

Mohamed Ibrahim Mohamed ◽

Ahmed Mahmoud El-Menoufi ◽

Eman Abed Ezz El-Regal ◽

Ahmed Mohamed Ali ◽

Khaled Mohamed Mansour ◽

...

Keyword(s):

Simulation Model ◽

Production Optimization ◽

Operating Conditions ◽

Gas Condensate ◽

Western Desert ◽

Design Parameters ◽

Compositional Approach ◽

Process Plant ◽

Black Oil

Abstract Field development planning of gas condensate fields using numerical simulation has many aspects to consider that may lead to a significant impact on production optimization. An important aspect is to account for the effects of network constraints and process plant operating conditions through an integrated asset model. This model should honor proper representation of the fluid within the reservoir, through the wells and up to the network and facility. Obaiyed is one of the biggest onshore gas field in Egypt, it is a highly heterogeneous gas condensate field located in the western desert of Egypt with more than 100 wells. Three initial condensate gas ratios are existing based on early PVT samples and production testing. The initial CGRs as follows;160, 115 and 42 STB/MMSCF. With continuous pressure depletion, the produced hydrocarbon composition stream changes, causing a deviation between the design parameters and the operating parameters of the equipment within the process plant, resulting in a decrease in the recovery of liquid condensate. Therefore, the facility engineers demand a dynamic update of a detailed composition stream to optimize the system and achieve greater economic value. The best way to obtain this compositional stream is by using a fully compositional integrated asset model. Utilizing a fully compositional model in Obaiyed is challenging, computationally expensive, and impractical, especially during the history match of the reservoir numerical model. In this paper, a case study for Obaiyed field is presented in which we used an alternative integrated asset modeling approach comprising a modified black-oil (MBO) that results in significant timesaving in the full-field reservoir simulation model. We then used a proper de-lumping scheme to convert the modified black oil tables into as many components as required by the surface network and process plant facility. The results of proposed approach are compared with a fully compositional approach for validity check. The results clearly identified the system bottlenecks. The model can be used to propose the best tie-in location of future wells in addition to providing first-pass flow assurance indications throughout the field's life and under different network configurations. The model enabled the facility engineers to keep the conditions of the surface facility within the optimized operating envelope throughout the field's lifetime.

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Dynamic Simulation of Petrochemical Wastewater Treatment Using Wastewater Plant Simulation Software

MATEC Web of Conferences ◽

10.1051/matecconf/201820303005 ◽

2018 ◽

Vol 203 ◽

pp. 03005

Author(s):

Idzham Fauzi Mohd Ariff ◽

Mardhiyah Bakir

Keyword(s):

Simulation Model ◽

Dynamic Simulation ◽

Stable Condition ◽

Oxygen Demand ◽

Simulation Software ◽

Petrochemical Plant ◽

Dynamic Simulation Model ◽

Plant Monitoring ◽

Plant Simulation

A dynamic simulation model was developed, calibrated and validated for a petrochemical plant in Terengganu, Malaysia. Calibration and validation of the model was conducted based on plant monitoring data spanning 3 years resulting in a model accuracy (RMSD) for effluent chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N) and total suspended solids (TSS) of ±11.7 mg/L, ±0.52 mg/L and ± 3.27 mg/L respectively. The simulation model has since been used for troubleshooting during plant upsets, planning of plant turnarounds and developing upgrade options. A case study is presented where the simulation model was used to assist in troubleshooting and rectification of a plant upset where ingress of a surfactant compound resulted in high effluent TSS and COD. The model was successfully used in the incident troubleshooting activities and provided critical insights that assisted the plant operators to quickly respond and bring back the system to normal, stable condition.

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Integrative Modeling Platform for Design and Control of an Adaptive Wind Turbine Blade

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems ◽

10.1115/dscc2018-9235 ◽

2018 ◽

Author(s):

Hamid Khakpour Nejadkhaki ◽

John F. Hall ◽

Minghui Zheng ◽

Teng Wu

Keyword(s):

Simulation Model ◽

Wind Turbine ◽

Real Time ◽

Turbine Blade ◽

Design Tool ◽

Real Time Control ◽

Time Control ◽

Partial Load ◽

And Control

A platform for the engineering design, performance, and control of an adaptive wind turbine blade is presented. This environment includes a simulation model, integrative design tool, and control framework. The authors are currently developing a novel blade with an adaptive twist angle distribution (TAD). The TAD influences the aerodynamic loads and thus, system dynamics. The modeling platform facilitates the use of an integrative design tool that establishes the TAD in relation to wind speed. The outcome of this design enables the transformation of the TAD during operation. Still, a robust control method is required to realize the benefits of the adaptive TAD. Moreover, simulation of the TAD is computationally expensive. It also requires a unique approach for both partial and full-load operation. A framework is currently being developed to relate the TAD to the wind turbine and its components. Understanding the relationship between the TAD and the dynamic system is crucial in the establishment of real-time control. This capability is necessary to improve wind capture and reduce system loads. In the current state of development, the platform is capable of maximizing wind capture during partial-load operation. However, the control tasks related to Region 3 and load mitigation are more complex. Our framework will require high-fidelity modeling and reduced-order models that support real-time control. The paper outlines the components of this framework that is being developed. The proposed platform will facilitate expansion and the use of these required modeling techniques. A case study of a 20 kW system is presented based upon the partial-load operation. The study demonstrates how the platform is used to design and control the blade. A low-dimensional aerodynamic model characterizes the blade performance. This interacts with the simulation model to predict the power production. The design tool establishes actuator locations and stiffness properties required for the blade shape to achieve a range of TAD configurations. A supervisory control model is implemented and used to demonstrate how the simulation model blade performs in the case study.

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